The biometric identification of persons on the basis of facial recognition is known. Digital pictures of a face can for example be compared with reference photographs of the face, which have been taken e.g. in accordance with the ICAO (International Civil Aviation Organization) according to the biometric standard ICAO 9303 (Photograph Guideline). Person recognition on the basis of non-normalized images is becoming increasingly widespread. The comparison between digital pictures and photos is undertaken routinely e.g. at many border stations. It is also possible to compare the digital picture of a person with a picture of the same person stored in a database, in order to allow this person access to systems, computers, applications on the Internet and the like. A method for biometric person recognition is for example described in DE 198 47 261 A1. Biometric person recognition methods are considered to be particularly reliable, because they use person-specific features.
In the relatively recent past, person recognition methods were developed, which are not based on the recognition of the features of an entire face, but rather only take account of the eye region of the persons. The use of the eye region (periocular region) for person recognition often leads to good results, because shiny surfaces usually occur less in this region of the face, unlike in the case of the forehead, cheeks and nose, for example. A comprehensive investigation of the performance of recognition methods based on the entire face and on the basis of the eye region was carried out by Dr. P. Jonathan Phillips at the National Institute of Standards and Technology, NIST. The results are presented at https://www.nist.gov/programs-projects/face-and-ocular-challenge-series-focs and show that the recognition rate is very dependent on the lighting conditions of the face and on the consistency of the facial expression. To this end, a so-called Good, Bad and Ugly (GBU) test was developed, which compares the recognition rate for good, moderate and poor image pairs (reference image and current image). The person recognition test parameters were set in such a manner in the test that the false acceptance rate or FAR (also false accept rate) was 0.001 using a given recognition method.
The FAR describes the likelihood or relative frequency, with which a person is recognized, although this is not the correct person. The FAR is generally considered to be the most important criterion for the quality of a biometric recognition method. An FAR of 0.001 means that in a statistical average of 1000 unauthorized access attempts, one will lead to success.
The investigations of Phillips have shown that even the best person recognition methods, which use facial recognition, at an FAR of 0.001 have a positive recognition rate of 0.98 in good lighting conditions and a good matching of the image pairs (Good), of 0.80 in moderate lighting conditions and moderate matching of the image pairs (Bad) and of 0.15 in poor lighting conditions and a poor matching of the image pairs (Ugly). In the scope of this test, the performance of the person recognition is also investigated on the basis of only the eye region (periocular recognition). The recognition rates were considerably poorer and lay in the order of magnitude of 47%, 17% and 5% for the test scenarios Good, Bad and Ugly. For person recognition on the basis of the eye region, particularly in the case of moderate and poor conditions, there is therefore room for improvement.
The invention is directed at a method for person recognition, which achieves better recognition rates than the prior art, such as in the case of moderate and poor lighting conditions.